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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS CHEMVIRO : Jurnal Kimia dan Ilmu Lingkungan
Pangesti, Windi
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Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Environmental Science

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Pemanfaatan Lato-Lato untuk Menentukan Besaran Percepatan Gravitasi Lokal Menggunakan Teori Getaran Harmonik Pangesti, Windi
Jurnal Kimia dan Ilmu Lingkungan: Chemviro Vol. 1 No. 1 (2023): Vol. 1 No. 1 (2023)
Publisher : Universitas Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56071/jkil.v1i1.561

Abstract

Abstract: Clackers is a fairly common toy these days. Clackers are used as a substitute for a pendulum in calculating the value of the local gravitational acceleration because a pendulum must have a weight suspended from a rope. The most basic method is to use a pendulum to calculate the local gravitational acceleration. The goal of this study was to determine the value of local gravitational acceleration at Bojonegoro University by using clackers in place of a pendulum. Experimental research is used to determine the local gravitational acceleration by proving the theory of earth's gravity. The acceleration of gravity is being studied at the Bojonegoro University because the value of gravity varies from place to place. At the Bojonegoro University, the acceleration of local gravity is calculated using two methods i.e. mathematical calculations and determining the slope between the length of the rope and the squared period. The gravitational acceleration calculated using the mean mathematical formula is Meanwhile, the acceleration due to gravity calculated from the slope value is . Keywords: gravitational acceleration; clackers Abstrak: Lato-lato merupakan mainan yang mudah dijumpai akhir-akhir ini. Lato-lato ternyata mampu dimanfaatkan sebagai pengganti bandul pada penentuan nilai percepatan gravitasi bumi lokal, karena syarat bandul yang digunakan adalah memiliki sebuah beban yang digantung di tali. Penentuan percepatan gravitasi bumi menggunakan bandul merupakan metode yang paling sederhana. Latar belakang dilakukan penelitian ini adalah untuk mengetahui nilai percepatan gravitasi lokal di Universitas Bojonegoro dengan memanfaatkan lato-lato sebagai pengganti bandul. Jenis penelitian yang digunakan untuk menentukan percepatan gravitasi lokal ini, yaitu penelitian eksperimental melalui pembuktian teori gravitasi bumi. Subjek yang diteliti adalah percepatan gravitasi bumi di Universitas Bojonegoro karena nilai gravitasi bumi pada setiap tempat berbeda. Dalam penentuan percepatan gravitasi bumi lokal di Universitas Bojonegoro dilakukan dengan dua pendekatan, yakni dengan penghitungan matematis dan penentuan dari slope antara panjang tali dengan periode kuadrat. Nilai percepatan gravitasi dari mean penghitungan secara matematis diperoleh sebesar . Sedangkan, nilai percepatan gravitasi dari nilai slope diperoleh sebesar . Kata kunci: percepatan gravitasi; lato-lato
Implementing LSTM-Based Deep Learning for Forecasting Food Commodity Prices with High Volatility: A Case Study in East Java Province Nensi, Andi Illa Erviani; Pangesti, Windi; Syukri, Nabila; Maida, Mahda Al; Notodiputro, Khairil Anwar
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.692

Abstract

Accurate food price forecasting is essential for maintaining market stability and food security. East Java Province was selected as the study area because it is one of Indonesia’s main food production centers and a major contributor to national inflation. This study compares three deep learning architectures LSTM, Bi-LSTM, and hybrid CNN-LSTM to forecast the prices of four key food commodities (red chili, shallots, medium-grade rice, and beef) in East Java. Hyperparameter tuning was performed using grid search, and performance was evaluated using MAPE, MAE, and RMSE. The results show that the Bi-LSTM model consistently provides the best performance compared to LSTM and CNN-LSTM across the four analyzed commodities. Based on MAPE, MAE, and RMSE values, Bi-LSTM achieved the lowest forecasting errors for all commodities. The MAPE values of Bi-LSTM were 1.73% for red chili, 0.60% for shallots, 0.23% for medium-grade rice, and 0.08% for beef, all of which were lower than those of LSTM and CNN-LSTM models. These findings highlight Bi-LSTM’s bidirectional architecture, which leverages contextual information from both past and future data sequences, making it the most robust and effective model for forecasting food prices under varying volatility. The study provides practical insights for policymakers and supply chain stakeholders in supporting price stability and food security.
Co-Authors Maida, Mahda Al Nensi, Andi Illa Erviani Syukri, Nabila